library(tidyverse)
library(viridis)
library(plotly)
library(p8105.datasets)
data(ny_noaa)
nynoaa <-
ny_noaa %>%
janitor::clean_names() %>%
separate(date, into = c("Year", "Month", "Day"), sep = "-") %>%
janitor::clean_names()
ploty 1
ny_df_1 =
nynoaa %>%
group_by(month,id) %>%
mutate(tmax = as.numeric(tmax)) %>%
mutate(tmin = as.numeric(tmin)) %>%
na.omit() %>%
summarise(mean_temp = mean(tmax)) %>%
ungroup
ny_df_1 %>%
plot_ly(x = ~month, y = ~mean_temp, type = "scatter", mode = "markers",
alpha = 0.5,
color = ~mean_temp,
text = ~id)
ploty 2
ny_df_2 =
nynoaa %>%
group_by(year,id) %>%
mutate(tmax = as.numeric(tmax)) %>%
mutate(tmin = as.numeric(tmin)) %>%
na.omit() %>%
summarise(mean_temp = mean(tmax)) %>%
ungroup
ny_df_2 %>%
plot_ly(x = ~year, y = ~mean_temp, color = ~year, type = "box")
## Warning in RColorBrewer::brewer.pal(N, "Set2"): n too large, allowed maximum for palette Set2 is 8
## Returning the palette you asked for with that many colors
## Warning in RColorBrewer::brewer.pal(N, "Set2"): n too large, allowed maximum for palette Set2 is 8
## Returning the palette you asked for with that many colors
plot 3
ny_df_3 <-nynoaa %>%
group_by(year, month) %>%
na.omit(tmax) %>%
na.omit(tmin) %>%
mutate(tmax_2 = as.numeric(tmax, na.rm = TRUE)) %>%
mutate(tmin_2 = as.numeric(tmin, na.rm = TRUE)) %>%
ungroup %>%
ggplot(aes(tmin_2,tmax_2))+
geom_hex(bins = 15)+
theme(legend.position = "bottom")
ggplotly(ny_df_3)